{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from config import *\n",
    "from map_wrapper import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020年5月\n"
     ]
    }
   ],
   "source": [
    "print(f'{year}年{month}月')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys\n",
    "sys.path.append('../../py')\n",
    "import db\n",
    "import weighted\n",
    "import inspect\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus']=False #用来正常显示负号\n",
    "%matplotlib inline\n",
    "from mpl_toolkits.basemap import Basemap\n",
    "import seaborn as sns\n",
    "import scipy.stats as stats\n",
    "import numpy as np\n",
    "import math\n",
    "from matplotlib.font_manager import _rebuild\n",
    "\n",
    "_rebuild() #reload一下"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn=db.get_conn()\n",
    "data_original=pd.read_sql(sql=f\"select * from _{year}{month:02} where monthly_salary>0 and monthly_salary<80000\", con=conn)\n",
    "\n",
    "data=data_original[~data_original.job_id.isin(error_job_ids)]\n",
    "\n",
    "del data['publish_date']\n",
    "del data['published_on_weekend']\n",
    "del data['title']\n",
    "#del data['company_title']\n",
    "#del data['company_description']\n",
    "del data['job_description']\n",
    "del data['job_id']\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "join_counts=[conn.execute(f\"select COUNT(1) from _{year}{month:02}\").fetchall()[0][0]]\n",
    "percents=[]\n",
    "for i in range(1,month-6+1):\n",
    "    sql=f\"select COUNT(1) from _{year}{month:02} a join _{year}{month-i:02} b on a.job_id = b.job_id\"\n",
    "    #print(sql)\n",
    "    count=conn.execute(sql).fetchall()[0][0]\n",
    "\n",
    "    join_counts.append(count)\n",
    "    subtract = join_counts[i-1]-join_counts[i]\n",
    "    percents.append(subtract*1.0/join_counts[i])\n",
    "\n",
    "percents.append(join_counts[-1]/join_counts[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[109155]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "join_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1.0]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "percents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#plt.pie(percents, labels=['1','2','3','4','5','6','7','7+'])\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "103220"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Common Functions\n",
    "def get_sub_stats_by_col(data, col):\n",
    "    categories=data[col].unique()\n",
    "    salary_mean=[]\n",
    "    salary_95_min=[]\n",
    "    salary_95_max=[]\n",
    "    salary_median=[]\n",
    "\n",
    "    count=[]\n",
    "    \n",
    "    categorys_out=[]\n",
    "    for category in categories:\n",
    "        #print(feature)\n",
    "        idata=data[data[col]==category]\n",
    "        headcount=idata.headcount.sum()\n",
    "        values = idata.monthly_salary.values\n",
    "        weights = idata.headcount.values\n",
    "        #print(str(headcount))\n",
    "        if headcount==0:\n",
    "            continue\n",
    "        \n",
    "        salary_mean.append(np.average(values, weights=weights))\n",
    "        \n",
    "\n",
    "        q = weighted.weighted_quantile(values,[0.025,0.5,0.975],weights)\n",
    "        salary_95_min.append(q[0])\n",
    "        salary_median.append(q[1])\n",
    "        salary_95_max.append(q[2])\n",
    "        count.append(idata.headcount.sum())\n",
    "        categorys_out.append(category)\n",
    "    sub_data=pd.DataFrame()\n",
    "    sub_data[col]=[c for c in categorys_out]\n",
    "    sub_data['salary_mean']=salary_mean\n",
    "    sub_data['salary_95_min']=salary_95_min\n",
    "    sub_data['salary_median']=salary_median\n",
    "    sub_data['salary_95_max']=salary_95_max\n",
    "    sub_data['head_count']=count\n",
    "    sub_data['percentage']=count/np.sum(count)\n",
    "    sub_data=sub_data.sort_values(by='salary_mean', ascending=False)\n",
    "\n",
    "    return sub_data\n",
    "\n",
    "data_format={\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\",\"salary_95_min\":\"{:.0f}\",\"salary_95_max\":\"{:.0f}\"}\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_87395d98_8b6a_11ea_a9de_701ce71031ef\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >career</th>        <th class=\"col_heading level0 col1\" >salary_mean</th>        <th class=\"col_heading level0 col2\" >salary_95_min</th>        <th class=\"col_heading level0 col3\" >salary_median</th>        <th class=\"col_heading level0 col4\" >salary_95_max</th>        <th class=\"col_heading level0 col5\" >head_count</th>        <th class=\"col_heading level0 col6\" >percentage</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >47</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow0_col0\" class=\"data row0 col0\" >CTO</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow0_col1\" class=\"data row0 col1\" >35936</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow0_col2\" class=\"data row0 col2\" >15969</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow0_col3\" class=\"data row0 col3\" >35833</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow0_col4\" class=\"data row0 col4\" >65448</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow0_col5\" class=\"data row0 col5\" >39</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow0_col6\" class=\"data row0 col6\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >50</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow1_col0\" class=\"data row1 col0\" >反作弊算法工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow1_col1\" class=\"data row1 col1\" >35062</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow1_col2\" class=\"data row1 col2\" >13000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow1_col3\" class=\"data row1 col3\" >37857</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow1_col4\" class=\"data row1 col4\" >40000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow1_col5\" class=\"data row1 col5\" >8</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow1_col6\" class=\"data row1 col6\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >36</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow2_col0\" class=\"data row2 col0\" >推荐算法工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow2_col1\" class=\"data row2 col1\" >34551</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow2_col2\" class=\"data row2 col2\" >14750</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow2_col3\" class=\"data row2 col3\" >32500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow2_col4\" class=\"data row2 col4\" >61917</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow2_col5\" class=\"data row2 col5\" >174</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow2_col6\" class=\"data row2 col6\" >0.06%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >55</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow3_col0\" class=\"data row3 col0\" >敏捷教练</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow3_col1\" class=\"data row3 col1\" >28344</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow3_col2\" class=\"data row3 col2\" >17500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow3_col3\" class=\"data row3 col3\" >30000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow3_col4\" class=\"data row3 col4\" >45000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow3_col5\" class=\"data row3 col5\" >32</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow3_col6\" class=\"data row3 col6\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >53</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow4_col0\" class=\"data row4 col0\" >数据科学家</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow4_col1\" class=\"data row4 col1\" >27761</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow4_col2\" class=\"data row4 col2\" >9219</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow4_col3\" class=\"data row4 col3\" >26429</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow4_col4\" class=\"data row4 col4\" >60000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow4_col5\" class=\"data row4 col5\" >175</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow4_col6\" class=\"data row4 col6\" >0.06%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row5\" class=\"row_heading level0 row5\" >11</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow5_col0\" class=\"data row5 col0\" >架构师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow5_col1\" class=\"data row5 col1\" >26184</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow5_col2\" class=\"data row5 col2\" >9000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow5_col3\" class=\"data row5 col3\" >25000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow5_col4\" class=\"data row5 col4\" >52528</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow5_col5\" class=\"data row5 col5\" >6738</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow5_col6\" class=\"data row5 col6\" >2.15%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row6\" class=\"row_heading level0 row6\" >18</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow6_col0\" class=\"data row6 col0\" >芯片</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow6_col1\" class=\"data row6 col1\" >26067</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow6_col2\" class=\"data row6 col2\" >9669</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow6_col3\" class=\"data row6 col3\" >22500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow6_col4\" class=\"data row6 col4\" >62500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow6_col5\" class=\"data row6 col5\" >194</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow6_col6\" class=\"data row6 col6\" >0.06%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row7\" class=\"row_heading level0 row7\" >27</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow7_col0\" class=\"data row7 col0\" >编译器开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow7_col1\" class=\"data row7 col1\" >24537</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow7_col2\" class=\"data row7 col2\" >11500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow7_col3\" class=\"data row7 col3\" >26429</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow7_col4\" class=\"data row7 col4\" >41167</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow7_col5\" class=\"data row7 col5\" >72</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow7_col6\" class=\"data row7 col6\" >0.02%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow8_col0\" class=\"data row8 col0\" >系统架构设计师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow8_col1\" class=\"data row8 col1\" >24335</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow8_col2\" class=\"data row8 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow8_col3\" class=\"data row8 col3\" >20833</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow8_col4\" class=\"data row8 col4\" >45456</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow8_col5\" class=\"data row8 col5\" >1366</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow8_col6\" class=\"data row8 col6\" >0.44%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row9\" class=\"row_heading level0 row9\" >37</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow9_col0\" class=\"data row9 col0\" >自然语言处理（NLP）</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow9_col1\" class=\"data row9 col1\" >24142</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow9_col2\" class=\"data row9 col2\" >9808</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow9_col3\" class=\"data row9 col3\" >22500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow9_col4\" class=\"data row9 col4\" >45000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow9_col5\" class=\"data row9 col5\" >437</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow9_col6\" class=\"data row9 col6\" >0.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row10\" class=\"row_heading level0 row10\" >28</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow10_col0\" class=\"data row10 col0\" >深度学习工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow10_col1\" class=\"data row10 col1\" >22647</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow10_col2\" class=\"data row10 col2\" >7550</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow10_col3\" class=\"data row10 col3\" >22500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow10_col4\" class=\"data row10 col4\" >51607</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow10_col5\" class=\"data row10 col5\" >566</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow10_col6\" class=\"data row10 col6\" >0.18%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row11\" class=\"row_heading level0 row11\" >13</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow11_col0\" class=\"data row11 col0\" >机器学习</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow11_col1\" class=\"data row11 col1\" >21826</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow11_col2\" class=\"data row11 col2\" >7000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow11_col3\" class=\"data row11 col3\" >18500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow11_col4\" class=\"data row11 col4\" >46560</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow11_col5\" class=\"data row11 col5\" >876</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow11_col6\" class=\"data row11 col6\" >0.28%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row12\" class=\"row_heading level0 row12\" >38</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow12_col0\" class=\"data row12 col0\" >SLAM</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow12_col1\" class=\"data row12 col1\" >21620</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow12_col2\" class=\"data row12 col2\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow12_col3\" class=\"data row12 col3\" >19286</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow12_col4\" class=\"data row12 col4\" >30000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow12_col5\" class=\"data row12 col5\" >34</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow12_col6\" class=\"data row12 col6\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row13\" class=\"row_heading level0 row13\" >43</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow13_col0\" class=\"data row13 col0\" >分布式</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow13_col1\" class=\"data row13 col1\" >20310</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow13_col2\" class=\"data row13 col2\" >8350</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow13_col3\" class=\"data row13 col3\" >20000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow13_col4\" class=\"data row13 col4\" >38200</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow13_col5\" class=\"data row13 col5\" >168</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow13_col6\" class=\"data row13 col6\" >0.05%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row14\" class=\"row_heading level0 row14\" >25</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow14_col0\" class=\"data row14 col0\" >图像算法工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow14_col1\" class=\"data row14 col1\" >20266</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow14_col2\" class=\"data row14 col2\" >9000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow14_col3\" class=\"data row14 col3\" >18500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow14_col4\" class=\"data row14 col4\" >40000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow14_col5\" class=\"data row14 col5\" >1834</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow14_col6\" class=\"data row14 col6\" >0.59%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row15\" class=\"row_heading level0 row15\" >23</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow15_col0\" class=\"data row15 col0\" >算法工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow15_col1\" class=\"data row15 col1\" >20200</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow15_col2\" class=\"data row15 col2\" >7500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow15_col3\" class=\"data row15 col3\" >17500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow15_col4\" class=\"data row15 col4\" >45000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow15_col5\" class=\"data row15 col5\" >8612</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow15_col6\" class=\"data row15 col6\" >2.75%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row16\" class=\"row_heading level0 row16\" >52</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow16_col0\" class=\"data row16 col0\" >搜索算法工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow16_col1\" class=\"data row16 col1\" >20134</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow16_col2\" class=\"data row16 col2\" >4320</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow16_col3\" class=\"data row16 col3\" >16000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow16_col4\" class=\"data row16 col4\" >53875</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow16_col5\" class=\"data row16 col5\" >69</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow16_col6\" class=\"data row16 col6\" >0.02%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row17\" class=\"row_heading level0 row17\" >15</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow17_col0\" class=\"data row17 col0\" >区块链开发</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow17_col1\" class=\"data row17 col1\" >19765</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow17_col2\" class=\"data row17 col2\" >7000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow17_col3\" class=\"data row17 col3\" >17500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow17_col4\" class=\"data row17 col4\" >42562</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow17_col5\" class=\"data row17 col5\" >679</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow17_col6\" class=\"data row17 col6\" >0.22%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row18\" class=\"row_heading level0 row18\" >49</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow18_col0\" class=\"data row18 col0\" >ADAS</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow18_col1\" class=\"data row18 col1\" >19577</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow18_col2\" class=\"data row18 col2\" >9525</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow18_col3\" class=\"data row18 col3\" >17850</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow18_col4\" class=\"data row18 col4\" >29166</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow18_col5\" class=\"data row18 col5\" >52</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow18_col6\" class=\"data row18 col6\" >0.02%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row19\" class=\"row_heading level0 row19\" >8</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow19_col0\" class=\"data row19 col0\" >驱动工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow19_col1\" class=\"data row19 col1\" >17990</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow19_col2\" class=\"data row19 col2\" >8000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow19_col3\" class=\"data row19 col3\" >17500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow19_col4\" class=\"data row19 col4\" >34950</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow19_col5\" class=\"data row19 col5\" >2750</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow19_col6\" class=\"data row19 col6\" >0.88%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row20\" class=\"row_heading level0 row20\" >16</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow20_col0\" class=\"data row20 col0\" >Hadoop工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow20_col1\" class=\"data row20 col1\" >17789</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow20_col2\" class=\"data row20 col2\" >6500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow20_col3\" class=\"data row20 col3\" >16500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow20_col4\" class=\"data row20 col4\" >37500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow20_col5\" class=\"data row20 col5\" >2417</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow20_col6\" class=\"data row20 col6\" >0.77%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow21_col0\" class=\"data row21 col0\" >移动开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow21_col1\" class=\"data row21 col1\" >17566</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow21_col2\" class=\"data row21 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow21_col3\" class=\"data row21 col3\" >14000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow21_col4\" class=\"data row21 col4\" >40000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow21_col5\" class=\"data row21 col5\" >2073</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow21_col6\" class=\"data row21 col6\" >0.66%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row22\" class=\"row_heading level0 row22\" >17</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow22_col0\" class=\"data row22 col0\" >游戏开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow22_col1\" class=\"data row22 col1\" >17311</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow22_col2\" class=\"data row22 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow22_col3\" class=\"data row22 col3\" >15000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow22_col4\" class=\"data row22 col4\" >42500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow22_col5\" class=\"data row22 col5\" >3543</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow22_col6\" class=\"data row22 col6\" >1.13%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row23\" class=\"row_heading level0 row23\" >26</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow23_col0\" class=\"data row23 col0\" >Unity3d开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow23_col1\" class=\"data row23 col1\" >17113</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow23_col2\" class=\"data row23 col2\" >5381</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow23_col3\" class=\"data row23 col3\" >15000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow23_col4\" class=\"data row23 col4\" >37500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow23_col5\" class=\"data row23 col5\" >763</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow23_col6\" class=\"data row23 col6\" >0.24%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row24\" class=\"row_heading level0 row24\" >41</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow24_col0\" class=\"data row24 col0\" >Cocos2d-x开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow24_col1\" class=\"data row24 col1\" >17049</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow24_col2\" class=\"data row24 col2\" >5385</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow24_col3\" class=\"data row24 col3\" >15000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow24_col4\" class=\"data row24 col4\" >38679</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow24_col5\" class=\"data row24 col5\" >314</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow24_col6\" class=\"data row24 col6\" >0.10%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row25\" class=\"row_heading level0 row25\" >34</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow25_col0\" class=\"data row25 col0\" >图像处理工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow25_col1\" class=\"data row25 col1\" >17010</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow25_col2\" class=\"data row25 col2\" >4180</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow25_col3\" class=\"data row25 col3\" >15000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow25_col4\" class=\"data row25 col4\" >39797</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow25_col5\" class=\"data row25 col5\" >691</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow25_col6\" class=\"data row25 col6\" >0.22%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row26\" class=\"row_heading level0 row26\" >20</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow26_col0\" class=\"data row26 col0\" >技术主管</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow26_col1\" class=\"data row26 col1\" >16839</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow26_col2\" class=\"data row26 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow26_col3\" class=\"data row26 col3\" >14000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow26_col4\" class=\"data row26 col4\" >55000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow26_col5\" class=\"data row26 col5\" >2013</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow26_col6\" class=\"data row26 col6\" >0.64%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row27\" class=\"row_heading level0 row27\" >14</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow27_col0\" class=\"data row27 col0\" >大数据</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow27_col1\" class=\"data row27 col1\" >16371</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow27_col2\" class=\"data row27 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow27_col3\" class=\"data row27 col3\" >15000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow27_col4\" class=\"data row27 col4\" >37500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow27_col5\" class=\"data row27 col5\" >5817</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow27_col6\" class=\"data row27 col6\" >1.86%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row28\" class=\"row_heading level0 row28\" >2</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow28_col0\" class=\"data row28 col0\" >iOS开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow28_col1\" class=\"data row28 col1\" >16295</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow28_col2\" class=\"data row28 col2\" >7000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow28_col3\" class=\"data row28 col3\" >14000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow28_col4\" class=\"data row28 col4\" >35000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow28_col5\" class=\"data row28 col5\" >1179</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow28_col6\" class=\"data row28 col6\" >0.38%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row29\" class=\"row_heading level0 row29\" >51</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow29_col0\" class=\"data row29 col0\" >游戏服务端开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow29_col1\" class=\"data row29 col1\" >15941</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow29_col2\" class=\"data row29 col2\" >2590</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow29_col3\" class=\"data row29 col3\" >16000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow29_col4\" class=\"data row29 col4\" >28708</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow29_col5\" class=\"data row29 col5\" >111</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow29_col6\" class=\"data row29 col6\" >0.04%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row30\" class=\"row_heading level0 row30\" >22</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow30_col0\" class=\"data row30 col0\" >人工智能</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow30_col1\" class=\"data row30 col1\" >15496</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow30_col2\" class=\"data row30 col2\" >3956</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow30_col3\" class=\"data row30 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow30_col4\" class=\"data row30 col4\" >37500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow30_col5\" class=\"data row30 col5\" >1447</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow30_col6\" class=\"data row30 col6\" >0.46%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row31\" class=\"row_heading level0 row31\" >44</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow31_col0\" class=\"data row31 col0\" >信号处理</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow31_col1\" class=\"data row31 col1\" >15222</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow31_col2\" class=\"data row31 col2\" >10000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow31_col3\" class=\"data row31 col3\" >12917</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow31_col4\" class=\"data row31 col4\" >27875</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow31_col5\" class=\"data row31 col5\" >54</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow31_col6\" class=\"data row31 col6\" >0.02%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row32\" class=\"row_heading level0 row32\" >31</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow32_col0\" class=\"data row32 col0\" >视觉软件工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow32_col1\" class=\"data row32 col1\" >14999</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow32_col2\" class=\"data row32 col2\" >7000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow32_col3\" class=\"data row32 col3\" >14000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow32_col4\" class=\"data row32 col4\" >26280</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow32_col5\" class=\"data row32 col5\" >373</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow32_col6\" class=\"data row32 col6\" >0.12%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row33\" class=\"row_heading level0 row33\" >46</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow33_col0\" class=\"data row33 col0\" >游戏客户端开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow33_col1\" class=\"data row33 col1\" >14975</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow33_col2\" class=\"data row33 col2\" >3750</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow33_col3\" class=\"data row33 col3\" >14000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow33_col4\" class=\"data row33 col4\" >35000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow33_col5\" class=\"data row33 col5\" >419</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow33_col6\" class=\"data row33 col6\" >0.13%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row34\" class=\"row_heading level0 row34\" >19</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow34_col0\" class=\"data row34 col0\" >Unity3D</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow34_col1\" class=\"data row34 col1\" >14947</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow34_col2\" class=\"data row34 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow34_col3\" class=\"data row34 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow34_col4\" class=\"data row34 col4\" >32500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow34_col5\" class=\"data row34 col5\" >1786</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow34_col6\" class=\"data row34 col6\" >0.57%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row35\" class=\"row_heading level0 row35\" >1</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow35_col0\" class=\"data row35 col0\" >Android开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow35_col1\" class=\"data row35 col1\" >14741</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow35_col2\" class=\"data row35 col2\" >6000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow35_col3\" class=\"data row35 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow35_col4\" class=\"data row35 col4\" >35000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow35_col5\" class=\"data row35 col5\" >14120</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow35_col6\" class=\"data row35 col6\" >4.51%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row36\" class=\"row_heading level0 row36\" >39</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow36_col0\" class=\"data row36 col0\" >机器人</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow36_col1\" class=\"data row36 col1\" >14549</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow36_col2\" class=\"data row36 col2\" >4208</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow36_col3\" class=\"data row36 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow36_col4\" class=\"data row36 col4\" >30000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow36_col5\" class=\"data row36 col5\" >384</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow36_col6\" class=\"data row36 col6\" >0.12%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row37\" class=\"row_heading level0 row37\" >42</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow37_col0\" class=\"data row37 col0\" >CAE</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow37_col1\" class=\"data row37 col1\" >14521</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow37_col2\" class=\"data row37 col2\" >4666</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow37_col3\" class=\"data row37 col3\" >15000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow37_col4\" class=\"data row37 col4\" >22916</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow37_col5\" class=\"data row37 col5\" >111</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow37_col6\" class=\"data row37 col6\" >0.04%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row38\" class=\"row_heading level0 row38\" >7</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow38_col0\" class=\"data row38 col0\" >DSP</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow38_col1\" class=\"data row38 col1\" >14114</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow38_col2\" class=\"data row38 col2\" >7000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow38_col3\" class=\"data row38 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow38_col4\" class=\"data row38 col4\" >39652</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow38_col5\" class=\"data row38 col5\" >576</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow38_col6\" class=\"data row38 col6\" >0.18%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row39\" class=\"row_heading level0 row39\" >12</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow39_col0\" class=\"data row39 col0\" >嵌入式软件开发</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow39_col1\" class=\"data row39 col1\" >13837</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow39_col2\" class=\"data row39 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow39_col3\" class=\"data row39 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow39_col4\" class=\"data row39 col4\" >31643</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow39_col5\" class=\"data row39 col5\" >6691</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow39_col6\" class=\"data row39 col6\" >2.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row40\" class=\"row_heading level0 row40\" >0</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow40_col0\" class=\"data row40 col0\" >软件工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow40_col1\" class=\"data row40 col1\" >13813</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow40_col2\" class=\"data row40 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow40_col3\" class=\"data row40 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow40_col4\" class=\"data row40 col4\" >30500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow40_col5\" class=\"data row40 col5\" >200926</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow40_col6\" class=\"data row40 col6\" >64.24%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row41\" class=\"row_heading level0 row41\" >35</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow41_col0\" class=\"data row41 col0\" >HTML5开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow41_col1\" class=\"data row41 col1\" >13658</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow41_col2\" class=\"data row41 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow41_col3\" class=\"data row41 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow41_col4\" class=\"data row41 col4\" >27344</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow41_col5\" class=\"data row41 col5\" >805</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow41_col6\" class=\"data row41 col6\" >0.26%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row42\" class=\"row_heading level0 row42\" >10</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow42_col0\" class=\"data row42 col0\" >大数据开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow42_col1\" class=\"data row42 col1\" >13426</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow42_col2\" class=\"data row42 col2\" >4912</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow42_col3\" class=\"data row42 col3\" >11714</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow42_col4\" class=\"data row42 col4\" >34950</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow42_col5\" class=\"data row42 col5\" >2864</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow42_col6\" class=\"data row42 col6\" >0.92%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row43\" class=\"row_heading level0 row43\" >30</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow43_col0\" class=\"data row43 col0\" >爬虫开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow43_col1\" class=\"data row43 col1\" >13352</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow43_col2\" class=\"data row43 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow43_col3\" class=\"data row43 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow43_col4\" class=\"data row43 col4\" >27500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow43_col5\" class=\"data row43 col5\" >590</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow43_col6\" class=\"data row43 col6\" >0.19%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row44\" class=\"row_heading level0 row44\" >29</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow44_col0\" class=\"data row44 col0\" >ETL</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow44_col1\" class=\"data row44 col1\" >13297</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow44_col2\" class=\"data row44 col2\" >7000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow44_col3\" class=\"data row44 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow44_col4\" class=\"data row44 col4\" >22500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow44_col5\" class=\"data row44 col5\" >1056</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow44_col6\" class=\"data row44 col6\" >0.34%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row45\" class=\"row_heading level0 row45\" >33</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow45_col0\" class=\"data row45 col0\" >机器视觉工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow45_col1\" class=\"data row45 col1\" >13044</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow45_col2\" class=\"data row45 col2\" >6000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow45_col3\" class=\"data row45 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow45_col4\" class=\"data row45 col4\" >28562</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow45_col5\" class=\"data row45 col5\" >489</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow45_col6\" class=\"data row45 col6\" >0.16%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row46\" class=\"row_heading level0 row46\" >32</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow46_col0\" class=\"data row46 col0\" >GIS</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow46_col1\" class=\"data row46 col1\" >12847</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow46_col2\" class=\"data row46 col2\" >6358</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow46_col3\" class=\"data row46 col3\" >11666</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow46_col4\" class=\"data row46 col4\" >25000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow46_col5\" class=\"data row46 col5\" >1632</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow46_col6\" class=\"data row46 col6\" >0.52%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row47\" class=\"row_heading level0 row47\" >3</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow47_col0\" class=\"data row47 col0\" >Web前端开发</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow47_col1\" class=\"data row47 col1\" >12688</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow47_col2\" class=\"data row47 col2\" >5250</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow47_col3\" class=\"data row47 col3\" >12500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow47_col4\" class=\"data row47 col4\" >27500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow47_col5\" class=\"data row47 col5\" >21671</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow47_col6\" class=\"data row47 col6\" >6.93%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row48\" class=\"row_heading level0 row48\" >6</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow48_col0\" class=\"data row48 col0\" >MES</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow48_col1\" class=\"data row48 col1\" >12567</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow48_col2\" class=\"data row48 col2\" >6158</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow48_col3\" class=\"data row48 col3\" >11500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow48_col4\" class=\"data row48 col4\" >24587</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow48_col5\" class=\"data row48 col5\" >753</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow48_col6\" class=\"data row48 col6\" >0.24%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row49\" class=\"row_heading level0 row49\" >5</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow49_col0\" class=\"data row49 col0\" >系统分析员</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow49_col1\" class=\"data row49 col1\" >12554</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow49_col2\" class=\"data row49 col2\" >3978</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow49_col3\" class=\"data row49 col3\" >11500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow49_col4\" class=\"data row49 col4\" >22500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow49_col5\" class=\"data row49 col5\" >504</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow49_col6\" class=\"data row49 col6\" >0.16%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row50\" class=\"row_heading level0 row50\" >24</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow50_col0\" class=\"data row50 col0\" >前端开发</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow50_col1\" class=\"data row50 col1\" >12344</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow50_col2\" class=\"data row50 col2\" >4000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow50_col3\" class=\"data row50 col3\" >11500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow50_col4\" class=\"data row50 col4\" >27500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow50_col5\" class=\"data row50 col5\" >5978</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow50_col6\" class=\"data row50 col6\" >1.91%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row51\" class=\"row_heading level0 row51\" >48</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow51_col0\" class=\"data row51 col0\" >遥感</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow51_col1\" class=\"data row51 col1\" >12085</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow51_col2\" class=\"data row51 col2\" >6500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow51_col3\" class=\"data row51 col3\" >12050</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow51_col4\" class=\"data row51 col4\" >20312</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow51_col5\" class=\"data row51 col5\" >90</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow51_col6\" class=\"data row51 col6\" >0.03%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row52\" class=\"row_heading level0 row52\" >54</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow52_col0\" class=\"data row52 col0\" >生物信息</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow52_col1\" class=\"data row52 col1\" >10978</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow52_col2\" class=\"data row52 col2\" >5556</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow52_col3\" class=\"data row52 col3\" >11500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow52_col4\" class=\"data row52 col4\" >16000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow52_col5\" class=\"data row52 col5\" >23</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow52_col6\" class=\"data row52 col6\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row53\" class=\"row_heading level0 row53\" >45</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow53_col0\" class=\"data row53 col0\" >网站架构设计师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow53_col1\" class=\"data row53 col1\" >10544</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow53_col2\" class=\"data row53 col2\" >4025</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow53_col3\" class=\"data row53 col3\" >7833</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow53_col4\" class=\"data row53 col4\" >30000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow53_col5\" class=\"data row53 col5\" >73</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow53_col6\" class=\"data row53 col6\" >0.02%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row54\" class=\"row_heading level0 row54\" >40</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow54_col0\" class=\"data row54 col0\" >小程序开发工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow54_col1\" class=\"data row54 col1\" >10134</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow54_col2\" class=\"data row54 col2\" >5000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow54_col3\" class=\"data row54 col3\" >9000</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow54_col4\" class=\"data row54 col4\" >20679</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow54_col5\" class=\"data row54 col5\" >662</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow54_col6\" class=\"data row54 col6\" >0.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_87395d98_8b6a_11ea_a9de_701ce71031eflevel0_row55\" class=\"row_heading level0 row55\" >4</th>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow55_col0\" class=\"data row55 col0\" >系统工程师</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow55_col1\" class=\"data row55 col1\" >9994</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow55_col2\" class=\"data row55 col2\" >3750</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow55_col3\" class=\"data row55 col3\" >8500</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow55_col4\" class=\"data row55 col4\" >24050</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow55_col5\" class=\"data row55 col5\" >4888</td>\n",
       "                        <td id=\"T_87395d98_8b6a_11ea_a9de_701ce71031efrow55_col6\" class=\"data row55 col6\" >1.56%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1c019150548>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_career=get_sub_stats_by_col(data,'career')\n",
    "data_career.style.format(data_format)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 程序员工资"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031ef\" ><thead>    <tr>        <th class=\"col_heading level0 col0\" >province</th>        <th class=\"col_heading level0 col1\" >salary_mean</th>        <th class=\"col_heading level0 col2\" >salary_95_min</th>        <th class=\"col_heading level0 col3\" >salary_median</th>        <th class=\"col_heading level0 col4\" >salary_95_max</th>        <th class=\"col_heading level0 col5\" >head_count</th>        <th class=\"col_heading level0 col6\" >percentage</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow0_col0\" class=\"data row0 col0\" >北京</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow0_col1\" class=\"data row0 col1\" >19273</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow0_col2\" class=\"data row0 col2\" >7000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow0_col3\" class=\"data row0 col3\" >17500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow0_col4\" class=\"data row0 col4\" >45000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow0_col5\" class=\"data row0 col5\" >24478</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow0_col6\" class=\"data row0 col6\" >7.83%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow1_col0\" class=\"data row1 col0\" >上海</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow1_col1\" class=\"data row1 col1\" >17477</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow1_col2\" class=\"data row1 col2\" >7000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow1_col3\" class=\"data row1 col3\" >15500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow1_col4\" class=\"data row1 col4\" >40000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow1_col5\" class=\"data row1 col5\" >51403</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow1_col6\" class=\"data row1 col6\" >16.44%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow2_col0\" class=\"data row2 col0\" >广东</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow2_col1\" class=\"data row2 col1\" >15416</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow2_col2\" class=\"data row2 col2\" >5833</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow2_col3\" class=\"data row2 col3\" >14000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow2_col4\" class=\"data row2 col4\" >35000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow2_col5\" class=\"data row2 col5\" >88275</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow2_col6\" class=\"data row2 col6\" >28.22%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow3_col0\" class=\"data row3 col0\" >浙江</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow3_col1\" class=\"data row3 col1\" >15032</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow3_col2\" class=\"data row3 col2\" >5750</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow3_col3\" class=\"data row3 col3\" >12500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow3_col4\" class=\"data row3 col4\" >35000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow3_col5\" class=\"data row3 col5\" >22131</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow3_col6\" class=\"data row3 col6\" >7.08%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow4_col0\" class=\"data row4 col0\" >四川</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow4_col1\" class=\"data row4 col1\" >12898</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow4_col2\" class=\"data row4 col2\" >5250</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow4_col3\" class=\"data row4 col3\" >12000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow4_col4\" class=\"data row4 col4\" >30000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow4_col5\" class=\"data row4 col5\" >15423</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow4_col6\" class=\"data row4 col6\" >4.93%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow5_col0\" class=\"data row5 col0\" >江苏</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow5_col1\" class=\"data row5 col1\" >12831</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow5_col2\" class=\"data row5 col2\" >5250</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow5_col3\" class=\"data row5 col3\" >12500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow5_col4\" class=\"data row5 col4\" >27500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow5_col5\" class=\"data row5 col5\" >33436</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow5_col6\" class=\"data row5 col6\" >10.69%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow6_col0\" class=\"data row6 col0\" >陕西</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow6_col1\" class=\"data row6 col1\" >12585</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow6_col2\" class=\"data row6 col2\" >5250</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow6_col3\" class=\"data row6 col3\" >12000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow6_col4\" class=\"data row6 col4\" >27500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow6_col5\" class=\"data row6 col5\" >9727</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow6_col6\" class=\"data row6 col6\" >3.11%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow7_col0\" class=\"data row7 col0\" >湖北</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow7_col1\" class=\"data row7 col1\" >12132</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow7_col2\" class=\"data row7 col2\" >5250</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow7_col3\" class=\"data row7 col3\" >11500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow7_col4\" class=\"data row7 col4\" >26000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow7_col5\" class=\"data row7 col5\" >14740</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow7_col6\" class=\"data row7 col6\" >4.71%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow8_col0\" class=\"data row8 col0\" >湖南</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow8_col1\" class=\"data row8 col1\" >11929</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow8_col2\" class=\"data row8 col2\" >5250</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow8_col3\" class=\"data row8 col3\" >11500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow8_col4\" class=\"data row8 col4\" >25000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow8_col5\" class=\"data row8 col5\" >7073</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow8_col6\" class=\"data row8 col6\" >2.26%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow9_col0\" class=\"data row9 col0\" >福建</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow9_col1\" class=\"data row9 col1\" >11356</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow9_col2\" class=\"data row9 col2\" >5000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow9_col3\" class=\"data row9 col3\" >10500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow9_col4\" class=\"data row9 col4\" >22500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow9_col5\" class=\"data row9 col5\" >5748</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow9_col6\" class=\"data row9 col6\" >1.84%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow10_col0\" class=\"data row10 col0\" >辽宁</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow10_col1\" class=\"data row10 col1\" >11343</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow10_col2\" class=\"data row10 col2\" >4000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow10_col3\" class=\"data row10 col3\" >9000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow10_col4\" class=\"data row10 col4\" >32155</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow10_col5\" class=\"data row10 col5\" >10009</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow10_col6\" class=\"data row10 col6\" >3.20%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow11_col0\" class=\"data row11 col0\" >天津</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow11_col1\" class=\"data row11 col1\" >11227</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow11_col2\" class=\"data row11 col2\" >5000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow11_col3\" class=\"data row11 col3\" >10000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow11_col4\" class=\"data row11 col4\" >22500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow11_col5\" class=\"data row11 col5\" >1974</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow11_col6\" class=\"data row11 col6\" >0.63%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow12_col0\" class=\"data row12 col0\" >重庆</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow12_col1\" class=\"data row12 col1\" >10878</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow12_col2\" class=\"data row12 col2\" >4500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow12_col3\" class=\"data row12 col3\" >9500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow12_col4\" class=\"data row12 col4\" >25764</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow12_col5\" class=\"data row12 col5\" >4228</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow12_col6\" class=\"data row12 col6\" >1.35%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow13_col0\" class=\"data row13 col0\" >安徽</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow13_col1\" class=\"data row13 col1\" >10837</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow13_col2\" class=\"data row13 col2\" >4500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow13_col3\" class=\"data row13 col3\" >10499</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow13_col4\" class=\"data row13 col4\" >22500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow13_col5\" class=\"data row13 col5\" >5027</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow13_col6\" class=\"data row13 col6\" >1.61%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow14_col0\" class=\"data row14 col0\" >海南</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow14_col1\" class=\"data row14 col1\" >9692</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow14_col2\" class=\"data row14 col2\" >5250</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow14_col3\" class=\"data row14 col3\" >9000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow14_col4\" class=\"data row14 col4\" >16087</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow14_col5\" class=\"data row14 col5\" >217</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow14_col6\" class=\"data row14 col6\" >0.07%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow15_col0\" class=\"data row15 col0\" >河南</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow15_col1\" class=\"data row15 col1\" >9623</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow15_col2\" class=\"data row15 col2\" >5000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow15_col3\" class=\"data row15 col3\" >9000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow15_col4\" class=\"data row15 col4\" >20000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow15_col5\" class=\"data row15 col5\" >2985</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow15_col6\" class=\"data row15 col6\" >0.95%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow16_col0\" class=\"data row16 col0\" >山东</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow16_col1\" class=\"data row16 col1\" >9234</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow16_col2\" class=\"data row16 col2\" >3750</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow16_col3\" class=\"data row16 col3\" >8500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow16_col4\" class=\"data row16 col4\" >20000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow16_col5\" class=\"data row16 col5\" >7268</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow16_col6\" class=\"data row16 col6\" >2.32%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow17_col0\" class=\"data row17 col0\" >江西</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow17_col1\" class=\"data row17 col1\" >9070</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow17_col2\" class=\"data row17 col2\" >3750</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow17_col3\" class=\"data row17 col3\" >9000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow17_col4\" class=\"data row17 col4\" >17500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow17_col5\" class=\"data row17 col5\" >1793</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow17_col6\" class=\"data row17 col6\" >0.57%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow18_col0\" class=\"data row18 col0\" >新疆</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow18_col1\" class=\"data row18 col1\" >8850</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow18_col2\" class=\"data row18 col2\" >5058</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow18_col3\" class=\"data row18 col3\" >9000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow18_col4\" class=\"data row18 col4\" >13394</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow18_col5\" class=\"data row18 col5\" >237</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow18_col6\" class=\"data row18 col6\" >0.08%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow19_col0\" class=\"data row19 col0\" >云南</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow19_col1\" class=\"data row19 col1\" >8478</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow19_col2\" class=\"data row19 col2\" >4500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow19_col3\" class=\"data row19 col3\" >8000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow19_col4\" class=\"data row19 col4\" >13500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow19_col5\" class=\"data row19 col5\" >2032</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow19_col6\" class=\"data row19 col6\" >0.65%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow20_col0\" class=\"data row20 col0\" >甘肃</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow20_col1\" class=\"data row20 col1\" >8367</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow20_col2\" class=\"data row20 col2\" >4639</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow20_col3\" class=\"data row20 col3\" >7500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow20_col4\" class=\"data row20 col4\" >12500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow20_col5\" class=\"data row20 col5\" >170</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow20_col6\" class=\"data row20 col6\" >0.05%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow21_col0\" class=\"data row21 col0\" >山西</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow21_col1\" class=\"data row21 col1\" >8363</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow21_col2\" class=\"data row21 col2\" >4945</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow21_col3\" class=\"data row21 col3\" >7000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow21_col4\" class=\"data row21 col4\" >15416</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow21_col5\" class=\"data row21 col5\" >213</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow21_col6\" class=\"data row21 col6\" >0.07%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow22_col0\" class=\"data row22 col0\" >内蒙古</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow22_col1\" class=\"data row22 col1\" >8238</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow22_col2\" class=\"data row22 col2\" >4708</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow22_col3\" class=\"data row22 col3\" >8000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow22_col4\" class=\"data row22 col4\" >15233</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow22_col5\" class=\"data row22 col5\" >86</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow22_col6\" class=\"data row22 col6\" >0.03%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow23_col0\" class=\"data row23 col0\" >吉林</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow23_col1\" class=\"data row23 col1\" >8164</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow23_col2\" class=\"data row23 col2\" >3750</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow23_col3\" class=\"data row23 col3\" >7500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow23_col4\" class=\"data row23 col4\" >12500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow23_col5\" class=\"data row23 col5\" >576</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow23_col6\" class=\"data row23 col6\" >0.18%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow24_col0\" class=\"data row24 col0\" >河北</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow24_col1\" class=\"data row24 col1\" >8089</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow24_col2\" class=\"data row24 col2\" >4500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow24_col3\" class=\"data row24 col3\" >7000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow24_col4\" class=\"data row24 col4\" >17500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow24_col5\" class=\"data row24 col5\" >1265</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow24_col6\" class=\"data row24 col6\" >0.40%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow25_col0\" class=\"data row25 col0\" >广西</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow25_col1\" class=\"data row25 col1\" >7895</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow25_col2\" class=\"data row25 col2\" >3750</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow25_col3\" class=\"data row25 col3\" >7000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow25_col4\" class=\"data row25 col4\" >14175</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow25_col5\" class=\"data row25 col5\" >1084</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow25_col6\" class=\"data row25 col6\" >0.35%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow26_col0\" class=\"data row26 col0\" >贵州</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow26_col1\" class=\"data row26 col1\" >7741</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow26_col2\" class=\"data row26 col2\" >5000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow26_col3\" class=\"data row26 col3\" >7500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow26_col4\" class=\"data row26 col4\" >12500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow26_col5\" class=\"data row26 col5\" >428</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow26_col6\" class=\"data row26 col6\" >0.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow27_col0\" class=\"data row27 col0\" >黑龙江</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow27_col1\" class=\"data row27 col1\" >7295</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow27_col2\" class=\"data row27 col2\" >3750</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow27_col3\" class=\"data row27 col3\" >7000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow27_col4\" class=\"data row27 col4\" >14162</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow27_col5\" class=\"data row27 col5\" >647</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow27_col6\" class=\"data row27 col6\" >0.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow28_col0\" class=\"data row28 col0\" >宁夏</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow28_col1\" class=\"data row28 col1\" >7068</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow28_col2\" class=\"data row28 col2\" >3750</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow28_col3\" class=\"data row28 col3\" >7000</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow28_col4\" class=\"data row28 col4\" >11500</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow28_col5\" class=\"data row28 col5\" >88</td>\n",
       "                        <td id=\"T_8d16c83a_8b6a_11ea_a899_701ce71031efrow28_col6\" class=\"data row28 col6\" >0.03%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1c0249e4b08>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_city=get_sub_stats_by_col(data,'province')\n",
    "#data_city.city=data_city.city.map(translate_dict)\n",
    "data_city.style.hide_index().format(data_format)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020年5月北京招收程序员24478人。2019年5月北京程序员平均工资19273元，工资中位数17500元，其中95%的人的工资介于7000元到45000元。\n",
      "\n",
      "2020年5月上海招收程序员51403人。2019年5月上海程序员平均工资17477元，工资中位数15500元，其中95%的人的工资介于7000元到40000元。\n",
      "\n",
      "2020年5月广东招收程序员88275人。2019年5月广东程序员平均工资15416元，工资中位数14000元，其中95%的人的工资介于5833元到35000元。\n",
      "\n",
      "2020年5月浙江招收程序员22131人。2019年5月浙江程序员平均工资15032元，工资中位数12500元，其中95%的人的工资介于5750元到35000元。\n",
      "\n",
      "2020年5月四川招收程序员15423人。2019年5月四川程序员平均工资12898元，工资中位数12000元，其中95%的人的工资介于5250元到30000元。\n",
      "\n",
      "2020年5月江苏招收程序员33436人。2019年5月江苏程序员平均工资12831元，工资中位数12500元，其中95%的人的工资介于5250元到27500元。\n",
      "\n",
      "2020年5月陕西招收程序员9727人。2019年5月陕西程序员平均工资12585元，工资中位数12000元，其中95%的人的工资介于5250元到27500元。\n",
      "\n",
      "2020年5月湖北招收程序员14740人。2019年5月湖北程序员平均工资12132元，工资中位数11500元，其中95%的人的工资介于5250元到26000元。\n",
      "\n",
      "2020年5月湖南招收程序员7073人。2019年5月湖南程序员平均工资11929元，工资中位数11500元，其中95%的人的工资介于5250元到25000元。\n",
      "\n",
      "2020年5月福建招收程序员5748人。2019年5月福建程序员平均工资11356元，工资中位数10500元，其中95%的人的工资介于5000元到22500元。\n",
      "\n",
      "2020年5月辽宁招收程序员10009人。2019年5月辽宁程序员平均工资11343元，工资中位数9000元，其中95%的人的工资介于4000元到32155元。\n",
      "\n",
      "2020年5月天津招收程序员1974人。2019年5月天津程序员平均工资11227元，工资中位数10000元，其中95%的人的工资介于5000元到22500元。\n",
      "\n",
      "2020年5月重庆招收程序员4228人。2019年5月重庆程序员平均工资10878元，工资中位数9500元，其中95%的人的工资介于4500元到25764元。\n",
      "\n",
      "2020年5月安徽招收程序员5027人。2019年5月安徽程序员平均工资10837元，工资中位数10499元，其中95%的人的工资介于4500元到22500元。\n",
      "\n",
      "2020年5月海南招收程序员217人。2019年5月海南程序员平均工资9692元，工资中位数9000元，其中95%的人的工资介于5250元到16087元。\n",
      "\n",
      "2020年5月河南招收程序员2985人。2019年5月河南程序员平均工资9623元，工资中位数9000元，其中95%的人的工资介于5000元到20000元。\n",
      "\n",
      "2020年5月山东招收程序员7268人。2019年5月山东程序员平均工资9234元，工资中位数8500元，其中95%的人的工资介于3750元到20000元。\n",
      "\n",
      "2020年5月江西招收程序员1793人。2019年5月江西程序员平均工资9070元，工资中位数9000元，其中95%的人的工资介于3750元到17500元。\n",
      "\n",
      "2020年5月新疆招收程序员237人。2019年5月新疆程序员平均工资8850元，工资中位数9000元，其中95%的人的工资介于5058元到13394元。\n",
      "\n",
      "2020年5月云南招收程序员2032人。2019年5月云南程序员平均工资8478元，工资中位数8000元，其中95%的人的工资介于4500元到13500元。\n",
      "\n",
      "2020年5月甘肃招收程序员170人。2019年5月甘肃程序员平均工资8367元，工资中位数7500元，其中95%的人的工资介于4639元到12500元。\n",
      "\n",
      "2020年5月山西招收程序员213人。2019年5月山西程序员平均工资8363元，工资中位数7000元，其中95%的人的工资介于4945元到15416元。\n",
      "\n",
      "2020年5月内蒙古招收程序员86人。2019年5月内蒙古程序员平均工资8238元，工资中位数8000元，其中95%的人的工资介于4708元到15233元。\n",
      "\n",
      "2020年5月吉林招收程序员576人。2019年5月吉林程序员平均工资8164元，工资中位数7500元，其中95%的人的工资介于3750元到12500元。\n",
      "\n",
      "2020年5月河北招收程序员1265人。2019年5月河北程序员平均工资8089元，工资中位数7000元，其中95%的人的工资介于4500元到17500元。\n",
      "\n",
      "2020年5月广西招收程序员1084人。2019年5月广西程序员平均工资7895元，工资中位数7000元，其中95%的人的工资介于3750元到14175元。\n",
      "\n",
      "2020年5月贵州招收程序员428人。2019年5月贵州程序员平均工资7741元，工资中位数7500元，其中95%的人的工资介于5000元到12500元。\n",
      "\n",
      "2020年5月黑龙江招收程序员647人。2019年5月黑龙江程序员平均工资7295元，工资中位数7000元，其中95%的人的工资介于3750元到14162元。\n",
      "\n",
      "2020年5月宁夏招收程序员88人。2019年5月宁夏程序员平均工资7068元，工资中位数7000元，其中95%的人的工资介于3750元到11500元。\n",
      "\n"
     ]
    }
   ],
   "source": [
    "describe(data_city,'程序员')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1040x1040 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_province_map(data_city,2000,'2019年5月中国大陆各省程序员工资')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
